BIM-Integrated Explainable Vision for Real-Time PPE Safety in Yemen’s Construction Sector

Abstract

This paper develops a BIM-integrated, explainable, and deployment-aware decision-support framework for real-time personal protective equipment (PPE) monitoring in Yemen’s construction sector. Its contribution is an integration-based decision-support artifact rather than a new PPE detection algorithm. The study addresses a persistent practical gap: many vision-based PPE systems can detect violations, yet they rarely convert image-level detections into auditable, location-aware, and managerially defensible interventions. Using a design science research approach, the paper re-specifies the original detection-centered concept as a socio-technical artifact composed of six tightly coupled layers: multimodal site capture, RF-DETR-based PPE perception, explanation generation, BIM spatial anchoring, AHP-TOPSIS-driven prioritization, and governance-oriented analytics. The assessment remains analytical, and field validation is left for future work. The framework formalizes an event schema that links each alert to confidence, explanation evidence, anchor confidence, zone semantics, response ownership, and closure status. It also introduces a resource-aware deployment path suited to fragile and connectivity-constrained projects by combining smartphone inspections, CCTV streams, offline buffering, staged BIM anchoring, and selective explanation triggering. The main contribution is therefore not merely improved PPE recognition; rather, it is the conversion of real-time vision outputs into trustworthy safety intelligence that supports prioritization, hotspot discovery, accountability, and progressive digital-twin readiness.